Coin and banknote acceptors are well known. One example of a coin acceptor is described in our GB-A-2 169 429. The acceptor includes a coin rundown path along which coins pass through a coin sensing station at which sensor coils perform a series of inductive tests on the coins in order to develop coin parameter signals which are indicative of the material and metallic content of the coin under test. The coin parameter signals are digitised and compared with stored coin data by means of a microcontroller to determine the acceptability or otherwise of the test coin. If the coin is found to be acceptable, the microcontroller operates an accept gate so that the coin is directed to an accept path. Otherwise, the accept gate remains inoperative and the coin is directed to a reject path.
In banknote validators, sensors detect characteristics of the banknote. For example, optical detectors can be used to detect the geometrical size of the banknote, its spectral response to a light source in transmission or reflection, or the presence of magnetic printing ink can be detected with an appropriate sensor. The parameter signals thus developed are digitised and compared with stored values in a similar way to the previously described prior art coin acceptor. The acceptability of the banknote is determined on the basis of the results of the comparison.
When a number of coins or banknotes of the same denomination are passed through an acceptor, successive values of coin or banknote parameter data are thus developed. When the distribution of the values of these signals is plotted as a graph, the result is a bell curve, with a central peak and tails on opposite sides. The shape of the graph may typically although not necessarily be Gaussian.
The distribution illustrates that for a money item, such as a coin or banknote of a particular denomination, the most probable value of the corresponding parameter signal lies at the peak of the bell curve, with a decreasing probability to either side. In prior coin and banknote validators, data is stored in a memory, corresponding to acceptable ranges of parameter signal for a particular denomination. The acceptor thus compares the value for a coin or banknote under test with the stored data to determine authenticity. The data may define windows in terms of upper and lower limit values, or as a mean value and a standard deviation, such that the window comprises a predetermined number of standard deviations about the mean. By making the stored windows narrow, an increased discrimination is provided between true money items and frauds. However, if the windows are made too narrow, the rejection rate of true money items increases, disadvantageously. The width of the windows is thus selected as a compromise between these two factors. Attempts to defraud coin or banknote validators typically involve the manufacture of facsimile coins or banknotes which cause the acceptor to produce parameter signals which lie within the stored acceptance windows.
In U.S. Pat. No. 5,355,989, a coin acceptor is described which switches from using a first normal acceptance window for a true coin, to a second narrower window when a coin parameter signal produced by testing a coin falls in a region of the normal window for the true coin corresponding to a low acceptance probability region for the coin concerned. A group of fraudulent coins may all have similar characteristics and they may cause the validator to produce parameter signals which lie within the normal window, but the parameter signals consistently have a value which is not centred on the high probability peak region of the window associated with the true coin but instead are centred on the lower probability tail regions of the bell curve distribution within the normal window. When the parameter signal falls within this low probability region, the second narrower window is then used for the next tested coin. If the next coin has a parameter falling in the narrower window it is a true coin but if not, it is a fraud which should be rejected. This approach seeks to prevent frauds carried out by the use of coins of a particular low value denomination, from a foreign currency set, with characteristics that correspond but are not exactly the same as a high value coin of the currency set that the acceptor is designed to accept. It will be understood that the foreign denomination coins exhibit their own generally Gaussian distribution of parameter signals, and if the low probability or tail region of this distribution partially overlaps a corresponding region of the distribution for the true coin that the acceptor is designed to accept, then the low value foreign coins will sometimes be accepted as true coins.
However, significant problems are unresolved by U.S. Pat. No. 5,355,989. In the disclosed arrangement, when a true coin is inserted, the system switches back from the second narrower window to the first normal acceptance window. If the next coin inserted is a foreign currency coin, if it has a parameter signal within the normal acceptance window, it will be accepted although the system will then switch to the second narrower window for the next coin under test. If the next coin tested is a true coin, it will be accepted and the system will switch back to the first window. The US Patent considers the possibility of counting groups of n coins before making the switch between the windows. Thus, with this system, it is possible to obtain acceptance of a significant number of foreign currency coins by alternating them with true coins either individually or in equal numbered groups of n coins. A further disadvantage is that the system is very slow because the foreign coins do not all produce an acceptance and so when a fraudster is attempting to use foreign coins they may be rejected a number of times as a result of falling outside of the first relatively wide acceptance window. However, the prior validator takes no account of the fraud attempt and will only respond when a fraudulent coin is in fact accepted.
WO 00/48138 discloses an arrangement to overcome these problems. In one embodiment, two security barrier ranges are introduced which lie outside the normal acceptance window. These security barrier ranges can be generally aligned with the peak of the distribution for the fraudulent coin. Even if the fraudulent coin produces a parameter signal outside of the normal acceptance window, should the parameter be within these barriers, the existence of the fraud attempt is detected, the coin is rejected, and the acceptor switches to the narrower acceptance window to reduce the risk of fraud.
In addition, WO 00/48138 discloses that in the event of a possible fraudulent attempt, the system is operable to compare any subsequent occurrences of the parameter signal with the narrower window for a predetermined time and then to revert to the normal acceptance window. Hence merely inserting a set number of true coins directly after a foreign coin will not then result in the system reverting to the normal acceptance window; a certain time must also have elapsed.
In spite of the more complex arrangement disclosed in WO 00/48138, the money item acceptor described therein has some shortfalls. A perseverant fraudster could make repeated fraudulent attempts and thus determine the number of true coins to be inserted or the amount of time to have lapsed before the use of the normal acceptance window is resumed. Also, particularly good counterfeit money items could be produced which when inserted into the money acceptor produce a Gaussian output with a narrow peak inside even the narrower acceptance window.